Why car companies are charging you a monthly fee for features you already own


Not long ago, buying a new car followed a somewhat predictable path. Do online research, pick a trim level, choose your options, go for a test drive, and sign the paperwork. Once you pull away from the dealership, everything on that window sticker is yours. Heated seats worked. Remote start worked. The features and packages you paid for were yours for as long as you owned the vehicle.

That was the deal. But that deal is changing. And most buyers don’t realize it until much further down the road.

Automakers are increasingly locking features behind monthly subscription fees, including things already physically built into the car you just purchased. The hardware is there. The wiring is there. Yet the software simply won’t activate unless you keep paying.

According to S&P Global Mobility, connected and subscription service revenue is expected to grow from roughly $6 billion in 2024 to around $15 billion by 2030. That money is coming from your pocket, and the industry is counting on you not to notice until the free trial runs out.

How Silicon Valley’s business model invaded your driveway

The subscription model didn’t start with cars, but it found them

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2025 BMW M5 Sedan Orange Leather
Credit: BMW

The logic automakers use is borrowed directly from the tech industry. As vehicles became more software-defined, it was perhaps inevitable that automakers would look at what Apple, Netflix, and Spotify had built and ask themselves the same question: why sell something once when you can charge for it every month?

What makes it particularly frustrating is that, as noted above, the hardware is already installed in the vehicle. The feature would work just fine on its own, but automakers have decided that activating it requires an ongoing payment.

Unlike your phone, which you may replace every few years, a car is something most people expect to own for a decade or more. Any subscription fees associated with the vehicle over the course of such a long ownership cycle can yield high profits for vehicle manufacturers. In effect, these monthly subscription models are attractive to automakers as a source of recurring revenue, especially as Americans are keeping their vehicles for longer and longer.

BMW was among the first to test this business model when, starting with its 2019 model year vehicles, it charged $80 per year for Apple CarPlay, a feature standard on vehicles costing a fraction of a BMW. The backlash was swift and public, to the point that BMW reversed course by December of that same year.

Then came the heated seats controversy (or, rather, the outright debacle) in 2022. At that time, BMW had introduced its ConnectedDrive functions-on-demand program in global markets, including the United Kingdom, Germany, and South Korea. The program charged owners around $18 per month to turn on their heated seats. The reaction again was swift and widespread, from both automotive industry veterans and everyday consumers. Many took their frustrations to social media.

By September 2023, BMW discontinued the heated seat subscription, with company executives later admitting that heated seats were “probably not the best way to start” with subscriptions.

Even though the backlash was bigger than BMW expected, they are still testing the waters with paid features. Today, it charges roughly between $5 and $20 per month for features like remote start, a drive recorder, and its Driving Assistant Plus system, depending on the model and generation. However, BMW is not alone.


A hand holding a fob opening a garage door remotely.


9 Things That Should Not be a Subscription

Selling your soul ten bucks at a time.

The features going behind a paywall

Remote start, driver assistance, and horsepower

On 2018 and later Toyota models, starting your vehicle remotely via a smartphone or smartwatch requires an active Remote Connect subscription, which runs $8 per month or $80 per year after the free trial expires. Even the physical key fob’s short-range remote start can be linked to this ecosystem on many Toyotas. Depending on the model, Remote Connect can be offered as part of a trial for anywhere from one to three years after a new vehicle purchase.

The subscription conversation gets more nuanced when it comes to advanced driver assistance features. GM’s Super Cruise and Ford’s BlueCruise are hands-free highway driving systems (pictured above) that both require ongoing subscriptions after a free trial period. At the time of this writing, Super Cruise runs $39.99 per month, while BlueCruise costs $49.99 per month, though Ford has introduced a one-time purchase option for those who want to avoid a recurring fee.

These systems arguably have a stronger case for the subscription model than remote start or heated seats, since they rely on continuously updated LiDAR maps, cloud connectivity, and regular over-the-air software improvements to function safely. However, when new vehicle prices have reached their highest point in history, consumers have a right to be irritated when they are asked to pay for something they believe would be part of the vehicle’s original purchase price.

To this end, the line between what is reasonable to charge for and what isn’t gets blurry. In the UK, Volkswagen began offering ID.3 owners a subscription to unlock the car’s full horsepower, charging around $22 per month for a 20-horsepower bump that the engine was already capable of producing from the factory. While this particular program has not come to North America, it once again signals where the industry’s mindset is headed.

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Lawmakers are pushing back

A step in the right direction, with notable exceptions

Vehicle manufacturers will likely continue down the path of paywalling more features and services, especially as vehicles become more software-defined. However, the practice won’t be without its uphill battles as it has drawn the attention of some lawmakers.

New York’s Senate Bill S5708, which passed both chambers of the state legislature and was awaiting Governor Kathy Hochul’s signature, would make it illegal for automakers and dealers to charge subscription fees for features that rely on hardware already installed in the vehicle. Similar legislation has been proposed in New Jersey and Massachusetts, though neither has been signed into law as of this writing.

The New York bill does include a notable exemption for features that require ongoing data, software support, or cloud connectivity from the automaker. In effect, systems like Super Cruise and BlueCruise would likely be excluded if the bill becomes law.

While none of this solves the problem nationally, it does signal that consumer frustration has reached a level that elected officials have taken notice. New York State Senator James Skoufis, who sponsored the bill, put it plainly: “If the automaker is building a feature into a car, for as long as cars have been invented, you’ve never had to pay a subscription to access those features.”


What you can do

If you are in the market for a new vehicle, ask the dealership about subscription services, what features they enable, and the fees that might be associated with them. Ask how long the trial subscription is specifically for the vehicle you are considering and what happens when it ends. The best time to understand what you are agreeing to is before you sign, not after the free trial runs out and a feature you rely on suddenly stops working.



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ZDNET’s key takeaways

  • Trusted quality data is the backbone of agentic AI.
  • Identifying high-impact workflows to assign to AI agents is key to scaling adoption.
  • Scaling agentic AI starts with rethinking how work gets done. 

Gartner forecasts that worldwide AI spending will total $2.5 trillion in 2026, a 44% year-over-year increase. Spending on AI platforms for data science and machine learning will reach $31 billion, and spending on AI data will reach $3 billion.

The global agentic AI market will reach $8.5 billion by the end of 2026 and nearly $40 billion by 2030, per Deloitte Digital. Organizations are rapidly accelerating their adoption of AI agents, with the current average utilization standing at 12 agents per organization, according to MuleSoft 2026 research. This rate is projected to increase by 67% over the next two years, reaching an average of 20 AI agents. 

Also: How to build better AI agents for your business – without creating trust issues

According to IDC, by 2026, 40% of all Global 2000 job roles will involve working with AI agents, redefining long-held traditional entry, mid, and senior level positions. But the journey will not be smooth. By 2027, companies that do not prioritize high-quality, AI-ready data will struggle to scale generative AI and agentic solutions, resulting in a 15% loss in productivity. While 2025 was the year of pilot experiments and small production deployments of agentic AI, 2026 is shaping up to be the year of scaling agentic AI. And to scale agentic AI, according to IDC’s forecast, companies will need trustworthy, accessible, and quality data. 

Scaling agentic AI adoption in business requires a strong data foundation, according to McKinsey research. Businesses can create high-impact workflows by using agents, but to do so, they must modernize their data architecture, improve data quality, and advance their operating models. 

McKinsey found that nearly two-thirds of enterprises worldwide have experimented with agents, but fewer than 10% have scaled them to deliver measurable value. The biggest obstacle to scaling agent adoption is poor data — eight in ten companies cite data limitations as a roadblock to scaling agentic AI. 

Also: AI agents are fast, loose, and out of control, MIT study finds

McKinsey identified the top data limitations as primary constraints that companies face when scaling AI, including: operating model and talent constraints, data limitations, ineffective change management, and tech platform limitations. 

Data is the backbone of agentic AI

Research shows that agentic AI needs a steady flow of high-quality, trusted data to accurately automate complex business workflows. Successful agentic AI also depends on a data architecture that can support autonomy — executing tasks without human intervention. 

Two agentic usage models are emerging: single-agent workflows (one agent using multiple tools) and multi-agent workflows (specialized agents collaborate). In each case, agents will rely on access to high-quality data. Data silos and fragmented data would lead to errors and poor agentic decision-making. 

Four steps for preparing your data 

McKinsey identified four coordinated steps that connect strategy, technology, and people in order to build strong foundational data capabilities. 

Also: Prolonged AI use can be hazardous to your health and work: 4 ways to stay safe

  1. Identify high-impact workflows to ‘agentify’. Focus on highly deterministic, repetitive tasks that deliver value as strong candidates for AI agents. 

  2. Modernize each layer of the data architecture for agents. The focus on modernization should support interoperability, easy access, and governance across systems. The vast majority of business applications do not share data across platforms. According to MuleSoft research, organizations are rapidly adopting autonomous systems. The average enterprise now manages 957 applications — rising to 1,057 for those furthest along in their agentic AI journey. Only 27% of these applications are currently connected, creating a significant challenge for IT leaders aiming to meet their near-term AI implementation goals. 

  3. Ensure that data quality is in place. Businesses must ensure that both structured and unstructured data, as well as agent-generated data, meet consistent standards for accuracy, lineage, and governance. Access to trusted data is a key obstacle. IT teams now spend an average of 36% of their time designing, building, and testing new custom integrations between systems and data. Custom work will not help scale AI adoption. The most significant obstacle to successful AI or AI agent deployment is data quality, cited as the top concern by 25% of organizations. Furthermore, almost all organizations (96%) struggle to use data from across the business for AI initiatives.  

  4. Build an operating and governance model for agentic AI. This is about rethinking how work gets done. Human roles will shift from execution to supervision and orchestration of agent-led workflows. In a hybrid work environment, governance will dictate how agents can operate autonomously in a trustworthy, transparent, and scaled manner. 

The work assigned to AI agents 

McKinsey highlighted the importance of identifying a few critical workflows that would be candidates for AI agents to own. To begin, an end-to-end workflow mapping would help identify opportunities for agentic use. McKinsey found that AI adoption is led by customer service, marketing, knowledge management, and IT. It is important to identify clear metrics that validate impact. Teams should identify the data that can be reused across tasks and workflows.

Also: These companies are actually upskilling their workers for AI – here’s how they do it

McKinsey concludes that having access to high-quality data is a strategic differentiator in the agentic AI era. Because agents will generate enormous amounts of data, data quality, lineage, and standardization will be even more important in the agentic enterprise. And as agentic systems scale, governance becomes the primary level for control. The data foundation will be the competitive advantage in the agentic era. 





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